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Assessing Credit Default using Logistic Regression and Multiple Discriminant Analysis: Empirical Evidence from Bosnia and Herzegovina

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  • Deni Memic

    (Department of Economics - Sarajevo School of Science and Technology)

Abstract

This article has an aim to assess credit default prediction on the banking market in Bosnia and Herzegovina nationwide as well as on its constitutional entities (Federation of Bosnia and Herzegovina and Republika Srpska). Ability to classify companies info different predefined groups or finding an appropriate tool which would replace human assessment in classifying companies into good and bad buckets has been one of the main interests on risk management researchers for a long time. We investigated the possibility and accuracy of default prediction using traditional statistical methods logistic regression (logit) and multiple discriminant analysis (MDA) and compared their predictive abilities. The results show that the created models have high predictive ability. For logit models, some variables are more influential on the default prediction than the others. Return on assets (ROA) is statistically significant in all four periods prior to default, having very high regression coefficients, or high impact on the model's ability to predict default. Similar results are obtained for MDA models. It is also found that predictive ability differs between logistic regression and multiple discriminant analysis.

Suggested Citation

  • Deni Memic, 2015. "Assessing Credit Default using Logistic Regression and Multiple Discriminant Analysis: Empirical Evidence from Bosnia and Herzegovina," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 13(1), pages 128-153.
  • Handle: RePEc:zna:indecs:v:13:y:2015:i:1:p:128-153
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    References listed on IDEAS

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    Cited by:

    1. Mabe, Queen Magadi & Lin, Wei, 2018. "Determinants of Corporate Failure: The Case of the Johannesburg Stock Exchange," MPRA Paper 88485, University Library of Munich, Germany.

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    More about this item

    Keywords

    Bosnia and Herzegovina; default prediction; logistic regression; multiple discriminant analysis; banking;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G53 - Financial Economics - - Household Finance - - - Financial Literacy

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